R version 4.0.3 (2020-10-10) – “Bunny-Wunnies Freak Out”

Packages used for NMDS: vegan (version 2.5-7)

Methods

The document shows a series of NMDS ordinations for reference benthic communities in Virginia with environmental characteristics overlaid to evaluate natural differences in community compositions across Virginia. These NMDS will support the Genus level IBI development process. This analysis is the first run of all of reference sites, reference West Virginia DEP sites, and sites that were deemed reference piedmont sites in Virginia. Reference sites were evaluated by regional biologists.

The dataset used includes all reference stations collected in Virginia that were deemed reference through a series or water quality parameter filters and regional biologist review. If stations appeared in the dataset more than 4 times, then the most recent 4 samples were used and the rest removed. Samples that had a total number of taxa below 100 collected at the time of sampling were also removed. Taxa that occurred in the dataset <= 5% of the time were removed. The data was log10 +1 transformed. Environmental factors were compiled for each station and used to plot over the NMDS to show environmental variation associated with the community matrix. The envfit function in Vegan was used to plot the continuous environmental variables. Some environmental variables like precipitation, slope, and elevation have not been calculated for all watersheds yet and will be added at a later date.

The first step was to read in the reference site bug taxa list and environmental factors dataset for each station. Join the environmental dataset with the bug dataset to account for multiple observations of each station and collection date and time.

Check to make sure the bug and environmental join was successful:

Number of rows in Community Matrix: 885

Number or rows in Environmental Matrix: 886

The data was log10+1 transformed. Rare taxa (<=5%) were removed.

NMDS Results for Non-Coastal Streams

## Run 0 stress 0.1736192 
## Run 1 stress 0.173711 
## ... Procrustes: rmse 0.003228835  max resid 0.04416222 
## Run 2 stress 0.1767676 
## Run 3 stress 0.1748688 
## Run 4 stress 0.1741778 
## Run 5 stress 0.1741189 
## ... Procrustes: rmse 0.004195746  max resid 0.05510594 
## Run 6 stress 0.1737059 
## ... Procrustes: rmse 0.002513765  max resid 0.05072623 
## Run 7 stress 0.1744884 
## Run 8 stress 0.1735867 
## ... New best solution
## ... Procrustes: rmse 0.001833516  max resid 0.04382191 
## Run 9 stress 0.1743853 
## Run 10 stress 0.1739469 
## ... Procrustes: rmse 0.002267956  max resid 0.05032217 
## Run 11 stress 0.1739365 
## ... Procrustes: rmse 0.004646453  max resid 0.0525155 
## Run 12 stress 0.1740398 
## ... Procrustes: rmse 0.00366061  max resid 0.05422801 
## Run 13 stress 0.1742292 
## Run 14 stress 0.1741323 
## Run 15 stress 0.1736095 
## ... Procrustes: rmse 0.002330499  max resid 0.04743859 
## Run 16 stress 0.1736815 
## ... Procrustes: rmse 0.003054224  max resid 0.05109447 
## Run 17 stress 0.1737134 
## ... Procrustes: rmse 0.002979084  max resid 0.05099102 
## Run 18 stress 0.1744563 
## Run 19 stress 0.1742569 
## Run 20 stress 0.1736935 
## ... Procrustes: rmse 0.003004436  max resid 0.0514255 
## Run 21 stress 0.1736302 
## ... Procrustes: rmse 0.002359916  max resid 0.04350769 
## Run 22 stress 0.1745518 
## Run 23 stress 0.1744939 
## Run 24 stress 0.1739928 
## ... Procrustes: rmse 0.003724485  max resid 0.09843851 
## Run 25 stress 0.17649 
## Run 26 stress 0.1763165 
## Run 27 stress 0.1763304 
## Run 28 stress 0.1741695 
## Run 29 stress 0.1762735 
## Run 30 stress 0.1736982 
## ... Procrustes: rmse 0.00360717  max resid 0.05158585 
## Run 31 stress 0.1745924 
## Run 32 stress 0.1741441 
## Run 33 stress 0.176818 
## Run 34 stress 0.17892 
## Run 35 stress 0.1747579 
## Run 36 stress 0.1744434 
## Run 37 stress 0.1777086 
## Run 38 stress 0.1740838 
## ... Procrustes: rmse 0.00292258  max resid 0.05097342 
## Run 39 stress 0.1763889 
## Run 40 stress 0.1765311 
## Run 41 stress 0.1777524 
## Run 42 stress 0.1736737 
## ... Procrustes: rmse 0.003569905  max resid 0.05152866 
## Run 43 stress 0.1744102 
## Run 44 stress 0.1774187 
## Run 45 stress 0.174176 
## Run 46 stress 0.177629 
## Run 47 stress 0.1745761 
## Run 48 stress 0.1735585 
## ... New best solution
## ... Procrustes: rmse 0.001530324  max resid 0.03535403 
## Run 49 stress 0.1768286 
## Run 50 stress 0.179401 
## Run 51 stress 0.173847 
## ... Procrustes: rmse 0.005148901  max resid 0.05260652 
## Run 52 stress 0.1739136 
## ... Procrustes: rmse 0.002367953  max resid 0.05158899 
## Run 53 stress 0.1740037 
## ... Procrustes: rmse 0.001774381  max resid 0.05122278 
## Run 54 stress 0.1793386 
## Run 55 stress 0.1740558 
## ... Procrustes: rmse 0.002350821  max resid 0.05079955 
## Run 56 stress 0.1782129 
## Run 57 stress 0.1747037 
## Run 58 stress 0.1744895 
## Run 59 stress 0.1741021 
## Run 60 stress 0.1741039 
## Run 61 stress 0.1745953 
## Run 62 stress 0.1739453 
## ... Procrustes: rmse 0.00288339  max resid 0.04959315 
## Run 63 stress 0.1770524 
## Run 64 stress 0.1738314 
## ... Procrustes: rmse 0.004992195  max resid 0.05256934 
## Run 65 stress 0.17491 
## Run 66 stress 0.1743824 
## Run 67 stress 0.1740452 
## ... Procrustes: rmse 0.004606132  max resid 0.09085112 
## Run 68 stress 0.1736759 
## ... Procrustes: rmse 0.002933027  max resid 0.05088994 
## Run 69 stress 0.1752478 
## Run 70 stress 0.1737831 
## ... Procrustes: rmse 0.002628352  max resid 0.04822576 
## Run 71 stress 0.1746318 
## Run 72 stress 0.1735876 
## ... Procrustes: rmse 0.002003344  max resid 0.03926261 
## Run 73 stress 0.1757354 
## Run 74 stress 0.1740912 
## Run 75 stress 0.1741092 
## Run 76 stress 0.1741614 
## Run 77 stress 0.173949 
## ... Procrustes: rmse 0.002876984  max resid 0.05097641 
## Run 78 stress 0.1744866 
## Run 79 stress 0.1740386 
## ... Procrustes: rmse 0.004665476  max resid 0.05475222 
## Run 80 stress 0.1737691 
## ... Procrustes: rmse 0.004455867  max resid 0.05220263 
## Run 81 stress 0.1736806 
## ... Procrustes: rmse 0.003266647  max resid 0.05122082 
## Run 82 stress 0.1741808 
## Run 83 stress 0.1740471 
## ... Procrustes: rmse 0.004764423  max resid 0.05494471 
## Run 84 stress 0.1736636 
## ... Procrustes: rmse 0.004314095  max resid 0.05217346 
## Run 85 stress 0.1736453 
## ... Procrustes: rmse 0.003407475  max resid 0.05161344 
## Run 86 stress 0.1744886 
## Run 87 stress 0.1739551 
## ... Procrustes: rmse 0.004850287  max resid 0.05258343 
## Run 88 stress 0.1736488 
## ... Procrustes: rmse 0.004233127  max resid 0.05212705 
## Run 89 stress 0.1741455 
## Run 90 stress 0.1735499 
## ... New best solution
## ... Procrustes: rmse 0.001408344  max resid 0.03949764 
## Run 91 stress 0.1736321 
## ... Procrustes: rmse 0.002391714  max resid 0.04387407 
## Run 92 stress 0.1736561 
## ... Procrustes: rmse 0.00237832  max resid 0.05095219 
## Run 93 stress 0.1804484 
## Run 94 stress 0.1747737 
## Run 95 stress 0.1787652 
## Run 96 stress 0.1756345 
## Run 97 stress 0.1749759 
## Run 98 stress 0.1744952 
## Run 99 stress 0.1793076 
## Run 100 stress 0.1737234 
## ... Procrustes: rmse 0.00258629  max resid 0.05103345 
## Run 101 stress 0.1740363 
## ... Procrustes: rmse 0.004670626  max resid 0.05469367 
## Run 102 stress 0.1736296 
## ... Procrustes: rmse 0.004424124  max resid 0.05212076 
## Run 103 stress 0.1741639 
## Run 104 stress 0.1738685 
## ... Procrustes: rmse 0.004863736  max resid 0.05226244 
## Run 105 stress 0.1739921 
## ... Procrustes: rmse 0.005149799  max resid 0.05454243 
## Run 106 stress 0.1736289 
## ... Procrustes: rmse 0.004457153  max resid 0.05216681 
## Run 107 stress 0.1793248 
## Run 108 stress 0.1789845 
## Run 109 stress 0.1741486 
## Run 110 stress 0.1752618 
## Run 111 stress 0.1736687 
## ... Procrustes: rmse 0.003828466  max resid 0.05186973 
## Run 112 stress 0.1744662 
## Run 113 stress 0.1736059 
## ... Procrustes: rmse 0.002177408  max resid 0.04375274 
## Run 114 stress 0.1741079 
## Run 115 stress 0.1744514 
## Run 116 stress 0.1791688 
## Run 117 stress 0.1741022 
## Run 118 stress 0.174059 
## Run 119 stress 0.174651 
## Run 120 stress 0.1744475 
## Run 121 stress 0.1736999 
## ... Procrustes: rmse 0.0007863275  max resid 0.009284998 
## ... Similar to previous best
## *** Solution reached
## 
## Call:
## metaMDS(comm = NoncoastalFive[, 6:107], k = 3, trymax = 1000) 
## 
## global Multidimensional Scaling using monoMDS
## 
## Data:     NoncoastalFive[, 6:107] 
## Distance: bray 
## 
## Dimensions: 3 
## Stress:     0.1735499 
## Stress type 1, weak ties
## Two convergent solutions found after 121 tries
## Scaling: centring, PC rotation, halfchange scaling 
## Species: expanded scores based on 'NoncoastalFive[, 6:107]'

##                     NMDS1    NMDS2     r2 Pr(>r)   
## Year             -0.99274 -0.12029 0.0160   0.19   
## JulianDate        0.40449 -0.91454 0.7224   0.01 **
## Latitude          0.49119  0.87105 0.0234   0.08 . 
## Longitude         0.57064  0.82120 0.0340   0.02 * 
## totalArea_sqMile  0.78844  0.61512 0.3327   0.01 **
## ELEVMEAN         -0.90407 -0.42738 0.2149   0.01 **
## SLPMEAN          -0.87177 -0.48991 0.1569   0.01 **
## wshdRain_mmyr     0.77970  0.62615 0.3135   0.01 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 99

Plot with Stations: Non-Coastal

Season: Non-Coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Season,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       Fall   Spring
## delta 0.6379 0.6358
## n     411    474   
## 
## Chance corrected within-group agreement A: 0.04938 
## Based on observed delta 0.6368 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Reference Type: Re-Pied or Ref

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$JRH_Final_Ref_Cod,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       Ref    Ref-Pied WVA   
## delta 0.6543 0.6468   0.5578
## n     685    99       101   
## 
## Chance corrected within-group agreement A: 0.04088 
## Based on observed delta 0.6425 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Ecoregion: Non-Coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$US_L3NAME,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       Blue Ridge Central Appalachians Northern Piedmont Piedmont
## delta 0.5952     0.5932               0.6494            0.6306  
## n     154        141                  125               213     
##       Ridge and Valley
## delta 0.6568          
## n     252             
## 
## Chance corrected within-group agreement A: 0.06158 
## Based on observed delta 0.6286 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Basin: Non-Coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Basin_Code,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##              Appomattox Chowan-Dismal James-Middle James-Upper New  
## delta 0.5578 0.5804     0.5794        0.6283       0.6536       0.65
## n     101    18         24            81           114         78   
##       Potomac-Lower Potomac-Shenandoah Rappahannock Roanoke Tennessee-Big Sandy
## delta 0.6482        0.6543             0.6404       0.6193  0.5996             
## n     40            41                 129          101     16                 
##       Tennessee-Clinch Tennessee-Holston Yadkin York 
## delta 0.6271           0.6244            0.5744 0.618
## n     50               53                4      35   
## 
## Chance corrected within-group agreement A: 0.0677 
## Based on observed delta 0.6245 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Admin Region: Non-Coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$ASSESS_REG,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##              BRRO   NRO    PRO    SWRO   VRO   
## delta 0.5578 0.6458 0.6637 0.6164 0.6323 0.6474
## n     101    258    198    55     156    117   
## 
## Chance corrected within-group agreement A: 0.05089 
## Based on observed delta 0.6358 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

##Bioregion: Non-Coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Bioregion,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       Mountain Piedmont
## delta 0.6498   0.648   
## n     547      338     
## 
## Chance corrected within-group agreement A: 0.03091 
## Based on observed delta 0.6492 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Sample Method: Non-Coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Gradient,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##              MACS   Riffle
## delta 0.5578 0.6056 0.6582
## n     101    39     745   
## 
## Chance corrected within-group agreement A: 0.03792 
## Based on observed delta 0.6445 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Stream Order: Non-Coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Order,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       0     1      2      3      4      5     
## delta   NaN 0.6343 0.6605 0.6351 0.6125 0.5681
## n     1     341    231    175    104    33    
## 
## Chance corrected within-group agreement A: 0.0501 
## Based on observed delta 0.6363 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Stream Order Categories: Non-coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$StreamCate,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       Large  No order Small 
## delta 0.6312   NaN    0.6541
## n     312    1        572   
## 
## Chance corrected within-group agreement A: 0.03561 
## Based on observed delta 0.646 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Water Quality Standard Class: Non-Coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$WQS_CLASS,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##              III    IV     V      VI    
## delta 0.5578 0.6502 0.6436 0.6302 0.6018
## n     101    310    184    87     203   
## 
## Chance corrected within-group agreement A: 0.06669 
## Based on observed delta 0.6252 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Natural Trout Water WQS: Non-Coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$WQS_TROUT,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##              Yes   
## delta 0.6771 0.6222
## n     595    290   
## 
## Chance corrected within-group agreement A: 0.01606 
## Based on observed delta 0.6591 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

#Ecoregion separated by Season

Bioregion and Season

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$BioregionSeason,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       MountainLargeFall MountainLargeSpring MountainNo orderFall
## delta 0.558             0.5802                NaN               
## n     82                86                  1                   
##       MountainSmallFall MountainSmallSpring PiedmontLargeFall
## delta 0.6103            0.5738              0.5816           
## n     156               222                 74               
##       PiedmontLargeSpring PiedmontSmallFall PiedmontSmallSpring
## delta 0.5963              0.5977            0.6061             
## n     70                  98                96                 
## 
## Chance corrected within-group agreement A: 0.1222 
## Based on observed delta 0.588 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

Bioregion, Stream Size and Season: Non-coastal

## 
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Bioregionsize,      distance = "bray") 
## 
## Dissimilarity index: bray 
## Weights for groups:  n 
## 
## Class means and counts:
## 
##       MountainLarge MountainNo order MountainSmall PiedmontLarge PiedmontSmall
## delta 0.605           NaN            0.6274        0.6195        0.6405       
## n     168           1                378           144           194          
## 
## Chance corrected within-group agreement A: 0.06734 
## Based on observed delta 0.6247 and expected delta 0.6699 
## 
## Significance of delta: 0.001 
## Permutation: free
## Number of permutations: 999

#Bioregion separated by Season